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@INPROCEEDINGS{kveton2010online,
author = {Branislav Kveton and Michal Valko and Matthai Phillipose and Ling
Huang},
title = {Online Semi-Supervised Perception: Real-Time Learning without Explicit
Feedback},
booktitle = {The Fourth IEEE Online Learning for Computer Vision Workshop in The
Twenty--Third IEEE Conference on Computer Vision and Pattern Recognition},
year = {2010},
address = {San Francisco, CA},
abstract = {This paper proposes an algorithm for real-time learning without explicit
feedback. The algorithm combines the ideas of semi-supervised learning
on graphs and online learning. In particular, it iteratively builds
a graphical representation of its world and updates it with observed
examples. Labeled examples constitute the initial bias of the algorithm
and are provided offline, and a stream of unlabeled examples is collected
online to update this bias. We motivate the algorithm, discuss how
to implement it efficiently, prove a regret bound on the quality
of its solutions, and apply it to the problem of real-time face recognition.
Our recognizer runs in real time, and achieves superior precision
and recall on 3 challenging video datasets.},
owner = {misovalko},
timestamp = {2010.06.06}
}